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Abstract We present a comparison of four different methods of measuring sensible (H) and latent (LE) heat fluxes for a year over a mixed grass prairie ecosystem in the Nebraska SandHills [eddy covariance (EC), energy balance/Bowen ratio (EBBR), residual energy (RES), modified Bowen ratio (MBR) methods]. Additionally, we developed a set of quality control criteria for each method and present a simplification to the traditional EBBR setup. Using EC as reference, all methods yielded similar estimates of yearly H (regression slopes (m) ~ 2% from unity; HEC > HEBBR, HRES, and HMBR). For yearly LE, EBBR and RES yielded similar estimates with EC (m ~ 2% from unity; LEEC LEMBR). At shorter time scales (~ hourly), moderate scatter was found about linear regression fits for H between EBBR and EC (R2 = 0.81), with smaller scatter between RES and MBR, and EC (R2 = 0.91). For LE, smaller scatter was also measured between EC, and EBBR and RES (R2 = 0.89 and 0.87, respectively), with the larger scatter between EC and MBR (R2 = 0.65). This suggests methods other than EC may be well suited to longer-term applications (≥ yearly), but have larger uncertainty on individual measurements.

A suite of generally applicable statistical methods based on empirical bootstrapping is presented for calculating uncertainty and testing the significance of quantitative differences in temperature and/or ice active site densities between ice nucleation temperature spectra derived from droplet freezing experiments. Such experiments are widely used to determine the heterogeneous ice nucleation properties and ice nucleation particle concentration spectra of different particle samples, as well as in studies of homogeneous freezing. Our methods avoid most of the assumptions and approximations inherent to existing approaches, and when sufficiently large sample sizes are used (approximately >150 droplets and >=1000 bootstrap samples in our system), can capture the full range of random variability and error in ice nucleation spectra. Applications include calculation of accurate confidence intervals and confidence bands, quantitative statistical testing of differences between observed freezing spectra, accurate subtraction of the background filtered water freezing signal, and calculation of a range of statistical parameters using data from a single droplet array freezing experiment if necessary. By providing additional statistical tools to the community, this work will improve the quality and accuracy of statistical tests and representations of uncertainty in future ice nucleation research, and will allow quantitative comparisons of the ice nucleation ability of different particles and surfaces.

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Ice nucleation abilities of surface collected mineral dust particles from the Sahara (SD) and Asia (AD) are investigated for the temperature (T) range 253–233 K and for supersaturated relative humidity (RH) conditions in the immersion freezing regime. The dust particles were also coated with a proxy of secondary organic aerosol (SOA) from the dark ozonolysis of α-pinene to better understand the influence of atmospheric coatings on the immersion freezing ability of mineral dust particles. The measurements are conducted on polydisperse particles in the size range 0.01–3 µm with three different ice nucleation chambers. Two of the chambers follow the continuous flow diffusion chamber (CFDC) principle (Portable Ice Nucleation Chamber, PINC) and the Colorado State University CFDC (CSU-CFDC), whereas the third was the Aerosol Interactions and Dynamics in the Atmosphere (AIDA) cloud expansion chamber. From observed activated fractions (AFs) and ice nucleation active site (INAS) densities, it is concluded within experimental uncertainties that there is no significant difference between the ice nucleation ability of the particular SD and AD samples examined. A small bias towards higher INAS densities for uncoated versus SOA-coated dusts is found but this is well within the 1σ (66 % prediction bands) region of the average fit to the data, which captures 75 % of the INAS densities observed in this study. Furthermore, no systematic differences are observed between SOA-coated and uncoated dusts in both SD and AD cases, regardless of coating thickness (3–60 nm). The results suggest that any differences observed are within the uncertainty of the measurements or differences in cloud chamber parameters such as size fraction of particles sampled, and residence time, as well as assumptions in using INAS densities to compare polydisperse aerosol measurements which may show variable composition with particle size. Coatings with similar properties to that of the SOA in this work and with coating thickness up to 60 nm are not expected to impede or enhance the immersion mode ice nucleation ability of mineral dust particles.

We present the laboratory results of immersion freezing efficiencies of cellulose particles at supercooled temperature (T) conditions. Three types of chemically homogeneous cellulose samples are used as surrogates that represent supermicron and submicron ice-nucleating plant structural polymers. These samples include microcrystalline cellulose (MCC), fibrous cellulose (FC) and nanocrystalline cellulose (NCC). Our immersion freezing dataset includes data from various ice nucleation measurement techniques available at 17 different institutions, including nine dry dispersion and 11 aqueous suspension techniques. With a total of 20 methods, we performed systematic accuracy and precision analysis of measurements from all 20 measurement techniques by evaluating T-binned (1 ∘C) data over a wide T range (−36 ∘C 

The second phase of the Fifth International Ice Nucleation Workshop (FIN-02) involved the gathering of a large number of researchers at the Karlsruhe Institute of Technology's Aerosol Interactions and Dynamics of the Atmosphere (AIDA) facility to promote characterization and understanding of ice nucleation measurements made by a variety of methods used worldwide. Compared to the previous workshop in 2007, participation was doubled, reflecting a vibrant research area. Experimental methods involved sampling of aerosol particles by direct processing ice nucleation measuring systems from the same volume of air in separate experiments using different ice nucleating particle (INP) types, and collections of aerosol particle samples onto filters or into liquid for sharing amongst measurement techniques that post-process these samples. In this manner, any errors introduced by differences in generation methods when samples are shared across laboratories were mitigated. Furthermore, as much as possible, aerosol particle size distribution was controlled so that the size limitations of different methods were minimized. The results presented here use data from the workshop to assess the comparability of immersion freezing measurement methods activating INPs in bulk suspensions, methods that activate INPs in condensation and/or immersion freezing modes as single particles on a substrate, continuous flow diffusion chambers (CFDCs) directly sampling and processing particles well above water saturation to maximize immersion and subsequent freezing of aerosol particles, and expansion cloud chamber simulations in which liquid cloud droplets were first activated on aerosol particles prior to freezing. The AIDA expansion chamber measurements are expected to be the closest representation to INP activation in atmospheric cloud parcels in these comparisons, due to exposing particles freely to adiabatic cooling.The different particle types used as INPs included the minerals illite NX and potassium feldspar (K-feldspar), two natural soil dusts representative of arable sandy loam (Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively, and a bacterial INP (Snomax®). Considered together, the agreement among post-processed immersion freezing measurements of the numbers and fractions of particles active at different temperatures following bulk collection of particles into liquid was excellent, with possible temperature uncertainties inferred to be a key factor in determining INP uncertainties. Collection onto filters for rinsing versus directly into liquid in impingers made little difference. For methods that activated collected single particles on a substrate at a controlled humidity at or above water saturation, agreement with immersion freezing methods was good in most cases, but was biased low in a few others for reasons that have not been resolved, but could relate to water vapor competition effects. Amongst CFDC-style instruments, various factors requiring (variable) higher supersaturations to achieve equivalent immersion freezing activation dominate the uncertainty between these measurements, and for comparison with bulk immersion freezing methods. When operated above water saturation to include assessment of immersion freezing, CFDC measurements often measured at or above the upper bound of immersion freezing device measurements, but often underestimated INP concentration in comparison to an immersion freezing method that first activates all particles into liquid droplets prior to cooling (the PIMCA-PINC device, or Portable Immersion Mode Cooling chAmber–Portable Ice Nucleation Chamber), and typically slightly underestimated INP number concentrations in comparison to cloud parcel expansions in the AIDA chamber; this can be largely mitigated when it is possible to raise the relative humidity to sufficiently high values in the CFDCs, although this is not always possible operationally.Correspondence of measurements of INPs among direct sampling and post-processing systems varied depending on the INP type. Agreement was best for Snomax® particles in the temperature regime colder than −10 °C, where their ice nucleation activity is nearly maximized and changes very little with temperature. At temperatures warmer than −10 °C, Snomax® INP measurements (all via freezing of suspensions) demonstrated discrepancies consistent with previous reports of the instability of its protein aggregates that appear to make it less suitable as a calibration INP at these temperatures. For Argentinian soil dust particles, there was excellent agreement across all measurement methods; measures ranged within 1 order of magnitude for INP number concentrations, active fractions and calculated active site densities over a 25 to 30 °C range and 5 to 8 orders of corresponding magnitude change in number concentrations. This was also the case for all temperatures warmer than −25 °C in Tunisian dust experiments. In contrast, discrepancies in measurements of INP concentrations or active site densities that exceeded 2 orders of magnitude across a broad range of temperature measurements found at temperatures warmer than −25 °C in a previous study were replicated for illite NX. Discrepancies also exceeded 2 orders of magnitude at temperatures of −20 to −25 °C for potassium feldspar (K-feldspar), but these coincided with the range of temperatures at which INP concentrations increase rapidly at approximately an order of magnitude per 2 °C cooling for K-feldspar.These few discrepancies did not outweigh the overall positive outcomes of the workshop activity, nor the future utility of this data set or future similar efforts for resolving remaining measurement issues. Measurements of the same materials were repeatable over the time of the workshop and demonstrated strong consistency with prior studies, as reflected by agreement of data broadly with parameterizations of different specific or general (e.g., soil dust) aerosol types. The divergent measurements of the INP activity of illite NX by direct versus post-processing methods were not repeated for other particle types, and the Snomax® data demonstrated that, at least for a biological INP type, there is no expected measurement bias between bulk collection and direct immediately processed freezing methods to as warm as −10 °C. Since particle size ranges were limited for this workshop, it can be expected that for atmospheric populations of INPs, measurement discrepancies will appear due to the different capabilities of methods for sampling the full aerosol size distribution, or due to limitations on achieving sufficient water supersaturations to fully capture immersion freezing in direct processing instruments. Overall, this workshop presents an improved picture of present capabilities for measuring INPs than in past workshops, and provides direction toward addressing remaining measurement issues.

Droplet freezing techniques (DFTs) have been used for half a century to measure the concentration of ice-nucleating particles (INPs) in the atmosphere and determine their freezing properties to understand the effects of INPs on mixed-phase clouds. The ice nucleation community has recently adopted droplet freezing assays as a commonplace experimental approach. These droplet freezing experiments are often limited by contamination that causes nonhomogeneous freezing of the pure water used to generate the droplets in the heterogeneous freezing temperature regime that is being measured. Interference from the early freezing of water is often overlooked and not fully reported, or measurements are restricted to analyzing the more ice-active INPs that freeze well above the temperature of the background water. However, this avoidance is not viable for analyzing the freezing behavior of less active INPs in the atmosphere that still have potentially important effects on cold-cloud microphysics. In this work we review a number of recent droplet freezing techniques that show great promise in reducing these interferences, and we report our own extensive series of measurements using similar methodologies. By characterizing the performance of different substrates on which the droplets are placed and of different pure water generation techniques, we recommend best practices to reduce these interferences. We tested different substrates, water sources, droplet matrixes, and droplet sizes to provide deeper insight into what methodologies are best suited for DFTs. Approaches for analyzing droplet freezing temperature spectra and accounting and correcting for the background pure water control spectrum are also presented. Finally, we propose experimental and data analysis procedures for future homogeneous and heterogeneous ice nucleation studies to promote a more uniform and reliable methodology that facilitates the ready intercomparison of ice-nucleating particles measured by DFTs.

The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme maximum θe. Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θe > 347 K. The median hit rate for maximum θe > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

Some biological particles, such as Snomax, are very active ice nucleating particles, inducing heterogeneous freezing in supercooled water at temperatures above −15 and up to −2 °C. Despite their exceptional freezing abilities, large uncertainties remain regarding the atmospheric abundance of biological ice nucleating particles, and their contribution to atmospheric ice nucleation. It has been suggested that small biological ice nucleating macromolecules or fragments can be carried on the surfaces of dust and other atmospheric particles. This could combine the atmospheric abundance of dust particles with the ice nucleating strength of biological material to create strongly enhanced and abundant ice nucleating surfaces in the atmosphere, with significant implications for the budget and distribution of atmospheric ice nucleating particles, and their consequent effects on cloud microphysics and mixed-phase clouds. The new critical surface area g framework that was developed by Beydoun et al. (2016) is extended to produce a heterogeneous ice nucleation mixing model that can predict the freezing behavior of multicomponent particle surfaces immersed in droplets. The model successfully predicts the immersion freezing properties of droplets containing Snomax bacterial particles across a mass concentration range of 7 orders of magnitude, by treating Snomax as comprised of two distinct distributions of heterogeneous ice nucleating activity. Furthermore, the model successfully predicts the immersion freezing behavior of a low-concentration mixture of Snomax and illite mineral particles, a proxy for the biological material–dust (bio-dust) mixtures observed in atmospheric aerosols. It is shown that even at very low Snomax concentrations in the mixture, droplet freezing at higher temperatures is still determined solely by the second less active and more abundant distribution of heterogeneous ice nucleating activity of Snomax, while freezing at lower temperatures is determined solely by the heterogeneous ice nucleating activity of pure illite. This demonstrates that in this proxy system, biological ice nucleating particles do not compromise their ice nucleating activity upon mixing with dust and no new range of intermediary freezing temperatures associated with the mixture of ice nucleating particles of differing activities is produced. The study is the first to directly examine the freezing behavior of a mixture of Snomax and illite and presents the first multicomponent ice nucleation model experimentally evaluated using a wide range of ice nucleating particle concentration mixtures in droplets.

Limited area (regional) models applied at high resolution over specific regions of interest are generally expected to more accurately capture the spatiotemporal variability of key meteorological and climate parameters. However, improved performance is not inevitable, and there remains a need to optimize use of numerical resources and to quantify the impact on simulation fidelity that derives from increased resolution. The application of regional models for climate forcing assessment is currently limited by the lack of studies quantifying the sensitivity to horizontal spatial resolution and the physical–dynamical–chemical schemes driving the simulations. Here we investigate model skill in simulating meteorological, chemical and aerosol properties as a function of spatial resolution, by applying the Weather Research and Forecasting model with coupled Chemistry (WRF-Chem) over eastern North America at different resolutions. Using Brier skill scores and other statistical metrics it is shown that enhanced resolution (from 60 to 12 km) improves model performance for all of the meteorological parameters and gas-phase concentrations considered, in addition to both mean and extreme aerosol optical depth (AOD) in three wavelengths in the visible relative to satellite observations, principally via increase of potential skill. Some of the enhanced model performance for AOD appears to be attributable to improved simulation of meteorological conditions and the concentration of key aerosol precursor gases (e.g., SO2 and NH3). Among other reasons, a dry bias in the specific humidity in the boundary layer and a substantial underestimation of total monthly precipitation in the 60 km simulations are identified as causes for the better performance of WRF-Chem simulations at 12 km.

Biomass burning is a large source of light-absorbing refractory black carbon (rBC) particles with a wide range of morphologies and sizes. The net radiative forcing from these particles is strongly dependent on the amount and composition of non-light-absorbing material internally mixed with the rBC and on the morphology of the mixed particles. Understanding how the mixing state and morphology of biomass-burning aerosol evolves in the atmosphere is critical for constraining the influence of these particles on radiative forcing and climate. We investigated the response of two commercial laser-based particle mass spectrometers, the vacuum ultraviolet (VUV) ablation LAAPTOF and the IR vaporization SP-AMS, to monodisperse biomass-burning particles as we sequentially coated the particles with secondary organic aerosol (SOA) from α-pinene ozonolysis. We studied three mobility-selected soot core sizes, each with a number of successively thicker coatings of SOA applied. Using IR laser vaporization, the SP-AMS had different changes in sensitivity to rBC compared to potassium as a function of applied SOA coatings. We show that this is due to different effective beam widths for the IR laser vaporization region of potassium versus black carbon. The SP-AMS's sensitivity to black carbon (BC) mass was not observed to plateau following successive SOA coatings, despite achieving high OA : BC mass ratios greater than 9. We also measured the ion fragmentation pattern of biomass-burning rBC and found it changed only slightly with increasing SOA mass. The average organic matter ion signal measured by the LAAPTOF demonstrated a positive correlation with the condensed SOA mass on individual particles, despite the inhomogeneity of the particle core compositions. This demonstrates that the LAAPTOF can obtain quantitative mass measurements of aged soot-particle composition from realistic biomass-burning particles with complex morphologies and composition.

Heterogeneous ice nucleation remains one of the outstanding problems in cloud physics and atmospheric science. Experimental challenges in properly simulating particle-induced freezing processes under atmospherically relevant conditions have largely contributed to the absence of a well-established parameterization of immersion freezing properties. Here, we formulate an ice active, surface-site-based stochastic model of heterogeneous freezing with the unique feature of invoking a continuum assumption on the ice nucleating activity (contact angle) of an aerosol particle's surface that requires no assumptions about the size or number of active sites. The result is a particle-specific property g that defines a distribution of local ice nucleation rates. Upon integration, this yields a full freezing probability function for an ice nucleating particle. Current cold plate droplet freezing measurements provide a valuable and inexpensive resource for studying the freezing properties of many atmospheric aerosol systems. We apply our g framework to explain the observed dependence of the freezing temperature of droplets in a cold plate on the concentration of the particle species investigated. Normalizing to the total particle mass or surface area present to derive the commonly used ice nuclei active surface (INAS) density (ns) often cannot account for the effects of particle concentration, yet concentration is typically varied to span a wider measurable freezing temperature range. A method based on determining what is denoted an ice nucleating species' specific critical surface area is presented and explains the concentration dependence as a result of increasing the variability in ice nucleating active sites between droplets. By applying this method to experimental droplet freezing data from four different systems, we demonstrate its ability to interpret immersion freezing temperature spectra of droplets containing variable particle concentrations. It is shown that general active site density functions, such as the popular ns parameterization, cannot be reliably extrapolated below this critical surface area threshold to describe freezing curves for lower particle surface area concentrations. Freezing curves obtained below this threshold translate to higher ns values, while the ns values are essentially the same from curves obtained above the critical area threshold; ns should remain the same for a system as concentration is varied. However, we can successfully predict the lower concentration freezing curves, which are more atmospherically relevant, through a process of random sampling from g distributions obtained from high particle concentration data. Our analysis is applied to cold plate freezing measurements of droplets containing variable concentrations of particles from NX illite minerals, MCC cellulose, and commercial Snomax bacterial particles. Parameterizations that can predict the temporal evolution of the frozen fraction of cloud droplets in larger atmospheric models are also derived from this new framework.

Assessing the ability of global and regional models to describe aerosol optical properties is essential to reducing uncertainty in aerosol direct radiative forcing in the contemporary climate and to improving confidence in future projections. Here we evaluate the performance of high-resolution simulations conducted using the Weather Research and Forecasting model with coupled with Chemistry (WRF-Chem) in capturing spatiotemporal variability of aerosol optical depth (AOD) and the Ångström exponent (AE) by comparison with ground- and space-based remotely sensed observations. WRF-Chem is run over eastern North America at a resolution of 12 km for a representative year (2008). A systematic positive bias in simulated AOD relative to observations is found (annual mean fractional bias (MFB) is 0.15 and 0.50 relative to MODIS (MODerate resolution Imaging Spectroradiometer) and AERONET, respectively), whereas the spatial variability is well captured during most months. The spatial correlation of observed and simulated AOD shows a clear seasonal cycle with highest correlation during summer months (r = 0.5–0.7) when the aerosol loading is large and more observations are available. The model is biased towards the simulation of coarse-mode aerosols (annual MFB for AE = −0.10 relative to MODIS and −0.59 for AERONET), but the spatial correlation for AE with observations is 0.3–0.5 during most months, despite the fact that AE is retrieved with higher uncertainty from the remote-sensing observations. WRF-Chem also exhibits high skill in identifying areas of extreme and non-extreme aerosol loading, and its ability to correctly simulate the location and relative intensity of extreme aerosol events (i.e., AOD > 75th percentile) varies between 30 and 70 % during winter and summer months, respectively.

Data from both laboratory studies and atmospheric measurements are used to develop an empirical parameterization for the immersion freezing activity of natural mineral dust particles. Measurements made with the Colorado State University (CSU) continuous flow diffusion chamber (CFDC) when processing mineral dust aerosols at a nominal 105% relative humidity with respect to water (RHw) are taken as a measure of the immersion freezing nucleation activity of particles. Ice active frozen fractions vs. temperature for dusts representative of Saharan and Asian desert sources were consistent with similar measurements in atmospheric dust plumes for a limited set of comparisons available. The parameterization developed follows the form of one suggested previously for atmospheric particles of non-specific composition in quantifying ice nucleating particle concentrations as functions of temperature and the total number concentration of particles larger than 0.5 μm diameter. Such an approach does not explicitly account for surface area and time dependencies for ice nucleation, but sufficiently encapsulates the activation properties for potential use in regional and global modeling simulations, and possible application in developing remote sensing retrievals for ice nucleating particles. A calibration factor is introduced to account for the apparent underestimate (by approximately 3, on average) of the immersion freezing fraction of mineral dust particles for CSU CFDC data processed at an RHw of 105% vs. maximum fractions active at higher RHw. Instrumental factors that affect activation behavior vs. RHw in CFDC instruments remain to be fully explored in future studies. Nevertheless, the use of this calibration factor is supported by comparison to ice activation data obtained for the same aerosols from Aerosol Interactions and Dynamics of the Atmosphere (AIDA) expansion chamber cloud parcel experiments. Further comparison of the new parameterization, including calibration correction, to predictions of the immersion freezing surface active site density parameterization for mineral dust particles, developed separately from AIDA experimental data alone, shows excellent agreement for data collected in a descent through a Saharan aerosol layer. These studies support the utility of laboratory measurements to obtain atmospherically relevant data on the ice nucleation properties of dust and other particle types, and suggest the suitability of considering all mineral dust as a single type of ice nucleating particle as a useful first-order approximation in numerical modeling investigations.

During the fourth Fire Lab at Missoula Experiment (FLAME-4, October–November 2012) a large variety of regionally and globally significant biomass fuels was burned at the US Forest Service Fire Sciences Laboratory in Missoula, Montana. The particle emissions were characterized by an extensive suite of instrumentation that measured aerosol chemistry, size distribution, optical properties, and cloud-nucleating properties. The trace gas measurements included high-resolution mass spectrometry, one- and two-dimensional gas chromatography, and open-path Fourier transform infrared (OP-FTIR) spectroscopy. This paper summarizes the overall experimental design for FLAME-4 – including the fuel properties, the nature of the burn simulations, and the instrumentation employed – and then focuses on the OP-FTIR results. The OP-FTIR was used to measure the initial emissions of 20 trace gases: CO2, CO, CH4, C2H2, C2H4, C3H6, HCHO, HCOOH, CH3OH, CH3COOH, glycolaldehyde, furan, H2O, NO, NO2, HONO, NH3, HCN, HCl, and SO2. These species include most of the major trace gases emitted by biomass burning, and for several of these compounds, this is the first time their emissions are reported for important fuel types. The main fire types included African grasses, Asian rice straw, cooking fires (open (three-stone), rocket, and gasifier stoves), Indonesian and extratropical peat, temperate and boreal coniferous canopy fuels, US crop residue, shredded tires, and trash. Comparisons of the OP-FTIR emission factors (EFs) and emission ratios (ERs) to field measurements of biomass burning verify that the large body of FLAME-4 results can be used to enhance the understanding of global biomass burning and its representation in atmospheric chemistry models. Crop residue fires are widespread globally and account for the most burned area in the US, but their emissions were previously poorly characterized. Extensive results are presented for burning rice and wheat straw: two major global crop residues. Burning alfalfa produced the highest average NH3 EF observed in the study (6.63 ± 2.47 g kg−1), while sugar cane fires produced the highest EF for glycolaldehyde (6.92 g kg−1) and other reactive oxygenated organic gases such as HCHO, HCOOH, and CH3COOH. Due to the high sulfur and nitrogen content of tires, they produced the highest average SO2 emissions (26.2 ± 2.2 g kg−1) and high NOx and HONO emissions. High variability was observed for peat fire emissions, but they were consistently characterized by large EFs for NH3 (1.82 ± 0.60 g kg−1) and CH4 (10.8 ± 5.6 g kg−1). The variability observed in peat fire emissions, the fact that only one peat fire had previously been subject to detailed emissions characterization, and the abundant emissions from tropical peatlands all impart high value to our detailed measurements of the emissions from burning three Indonesian peat samples. This study also provides the first EFs for HONO and NO2 for Indonesian peat fires. Open cooking fire emissions of HONO and HCN are reported for the first time, and the first emissions data for HCN, NO, NO2, HONO, glycolaldehyde, furan, and SO2 are reported for "rocket" stoves: a common type of improved cookstove. The HCN / CO emission ratios for cooking fires (1.72 × 10−3 ± 4.08 × 10−4) and peat fires (1.45 × 10−2 ± 5.47 × 10−3) are well below and above the typical values for other types of biomass burning, respectively. This would affect the use of HCN / CO observations for source apportionment in some regions. Biomass burning EFs for HCl are rare and are reported for the first time for burning African savanna grasses. High emissions of HCl were also produced by burning many crop residues and two grasses from coastal ecosystems. HCl could be the main chlorine-containing gas in very fresh smoke, but rapid partitioning to aerosol followed by slower outgassing probably occurs.

During the measurement campaign FROST 2 (FReezing Of duST 2), the Leipzig Aerosol Cloud Interaction Simulator (LACIS) was used to investigate the influence of various surface modifications on the ice nucleating ability of Arizona Test Dust (ATD) particles in the immersion freezing mode. The dust particles were exposed to sulfuric acid vapor, to water vapor with and without the addition of ammonia gas, and heat using a thermodenuder operating at 250 °C. Size selected, quasi monodisperse particles with a mobility diameter of 300 nm were fed into LACIS and droplets grew on these particles such that each droplet contained a single particle. Temperature dependent frozen fractions of these droplets were determined in a temperature range between −40 °C ≤T≤−28 °C. The pure ATD particles nucleated ice over a broad temperature range with their freezing behavior being separated into two freezing branches characterized through different slopes in the frozen fraction vs. temperature curves. Coating the ATD particles with sulfuric acid resulted in the particles' IN potential significantly decreasing in the first freezing branch (T>−35 °C) and a slight increase in the second branch (T≤−35 °C). The addition of water vapor after the sulfuric acid coating caused the disappearance of the first freezing branch and a strong reduction of the IN ability in the second freezing branch. The presence of ammonia gas during water vapor exposure had a negligible effect on the particles' IN ability compared to the effect of water vapor. Heating in the thermodenuder led to a decreased IN ability of the sulfuric acid coated particles for both branches but the additional heat did not or only slightly change the IN ability of the pure ATD and the water vapor exposed sulfuric acid coated particles. In other words, the combination of both sulfuric acid and water vapor being present is a main cause for the ice active surface features of the ATD particles being destroyed. A possible explanation could be the chemical transformation of ice active metal silicates to metal sulfates. The strongly enhanced reaction between sulfuric acid and dust in the presence of water vapor and the resulting significant reductions in IN potential are of importance for atmospheric ice cloud formation. Our findings suggest that the IN concentration can decrease by up to one order of magnitude for the conditions investigated.

The ability of coated mineral dust particles to act as ice nuclei (IN) was investigated at LACIS (Leipzig Aerosol Cloud Interaction Simulator) during the FROST1- and FROST2-campaigns (Freezing of dust). Sulphuric acid was condensed on the particles which afterwards were optionally humidified, treated with ammonia vapour and/or heat. By means of aerosol mass spectrometry we found evidence that processing of mineral dust particles with sulphuric acid leads to surface modifications of the particles. These surface modifications are most likely responsible for the observed reduction of the IN activation of the particles. The observed particle mass spectra suggest that different treatments lead to different chemical reactions on the particle surface. Possible chemical reaction pathways and products are suggested and the implications on the IN efficiency of the treated dust particles are discussed.

During the FROST-2 (FReezing Of duST) measurement campaign conducted at the Leipzig Aerosol Cloud Interaction Simulator (LACIS), we investigated changes in the ice nucleation properties of 300 nm Arizona Test Dust mineral particles following thermochemical processing by varying amounts and combinations of exposure to sulphuric acid vapour, ammonia gas, water vapour, and heat. The processed particles' heterogeneous ice nucleation properties were determined in both the water subsaturated and supersaturated humidity regimes at −30 °C and −25 °C using Colorado State University's continuous flow diffusion chamber. The amount of sulphuric acid coating material was estimated by an aerosol mass spectrometer and from CCN-derived hygroscopicity measurements. The condensation of sulphuric acid decreased the dust particles' ice nucleation ability in proportion to the amount of sulphuric acid added. Heating the coated particles in a thermodenuder at 250 °C – intended to evaporate the sulphuric acid coating – reduced their freezing ability even further. We attribute this behaviour to accelerated acid digestion of ice active surface sites by heat. Exposing sulphuric acid coated dust to ammonia gas produced particles with similarly poor freezing potential; however a portion of their ice nucleation ability could be restored after heating in the thermodenuder. In no case did any combination of thermochemical treatments increase the ice nucleation ability of the coated mineral dust particles compared to unprocessed dust. These first measurements of the effect of identical chemical processing of dust particles on their ice nucleation ability under both water subsaturated and mixed-phase supersaturated cloud conditions revealed that ice nucleation was more sensitive to all coating treatments in the water subsaturated regime. The results clearly indicate irreversible impairment of ice nucleation activity in both regimes after condensation of concentrated sulphuric acid. This implies that the sulphuric acid coating caused permanent chemical and/or physical modification of the ice active surface sites; the possible dissolution of the coating during droplet activation did not restore all immersion/condensation-freezing ability.

Atmospheric mineral dust particles can alter cloud properties and thus climate by acting as cloud condensation nuclei (CCN) that form cloud droplets. The CCN activation properties of various calcium mineral dust particles were studied experimentally to investigate the consequences of field observations showing the segregation of sulphate from nitrate and chloride between individual aged Asian dust particles, and the enrichment of oxalic acid in Asian dust. Each mineral's observed apparent hygroscopicity was primarily controlled by its solubility, which determines the degree to which the mineral's intrinsic hygroscopicity can be expressed. The significant increase in hygroscopicity caused by mixing soluble hygroscopic material with insoluble mineral particles is also presented. Insoluble minerals including calcium carbonate, representing fresh unprocessed dust, and calcium sulphate, representing atmospherically processed dust, had similarly small apparent hygroscopicities. Their activation is accurately described by a deliquescence limit following the Kelvin effect and corresponded to an apparent single-hygroscopicity parameter, κ, of ~0.001. Soluble calcium chloride and calcium nitrate, representing atmospherically processed mineral dust particles, were much more hygroscopic, activating similar to ammonium sulphate with κ~0.5. Calcium oxalate monohydrate (κ=0.05) was significantly less CCN-active than oxalic acid (κ=0.3), but not as inactive as its low solubility would predict. These results indicate that the common assumption that all mineral dust particles become more hygroscopic and CCN-active after atmospheric processing should be revisited. Calcium sulphate and calcium oxalate are two realistic proxies for aged mineral dust that remain non-hygroscopic. The dust's apparent hygroscopicity will be controlled by its chemical mixing state, which is determined by its mineralogy and the chemical reaction pathways it experiences during transport.

The accumulation of secondary acids and ammonium on individual mineral dust particles during ACE-Asia has been measured with an online single-particle mass spectrometer, the ATOFMS. Changes in the amounts of sulphate, nitrate, and chloride mixed with dust particles correlate with air masses from different source regions. The uptake of secondary acids depended on the individual dust particle mineralogy; high amounts of nitrate accumulated on calcium-rich dust while high amounts of sulphate accumulated on aluminosilicate-rich dust. Oxidation of S(IV) to S(VI) by iron in the aluminosilicate dust is a possible explanation for this enrichment of sulphate, which has important consequences for the fertilization of remote oceans by soluble iron. This study shows the segregation of sulphate from nitrate and chloride in individual aged dust particles for the first time. A transport and aging timeline provides an explanation for the observed segregation. Our data suggests that sulphate became mixed with the dust first. This implies that the transport pathway is more important than the reaction kinetics in determining which species accumulate on mineral dust. Early in the study, dust particles in volcanically influenced air masses were mixed predominately with sulphate. Dust mixed with chloride then dominated over sulphate and nitrate when a major dust front reached the R. V. Ronald Brown. We hypothesize that the rapid increase in chloride on dust was due to mixing with HCl(g) released from acidified sea salt particles induced by heterogeneous reaction with volcanic SO2(g), prior to the arrival of the dust front. The amount of ammonium mixed with dust correlated strongly with the total amount of secondary acid reaction products in the dust. Submicron dust and ammonium sulphate were internally mixed, contrary to frequent reports that they exist as external mixtures. The size distribution of the mixing state of dust with these secondary species validates previous mechanisms of the atmospheric processing of dust and generally agrees with simulated aerosol chemistry from the STEM-2K3 model. This series of novel results has important implications for improving the treatment of dust in global chemistry models and highlights a number of key processes that merit further investigation through laboratory and field studies.

The room temperature kinetics of gas-phase ozone loss via heterogeneous interactions with thin alumina films has been studied in real-time using 254nm absorption spectroscopy to monitor ozone concentrations. The films were prepared from dispersions of fine alumina powder in methanol and their surface areas were determined by an in situ procedure using adsorption of krypton at 77K. The alumina was found to lose reactivity with increasing ozone exposure. However, some of the lost reactivity could be recovered over timescales of days in an environment free of water, ozone and carbon dioxide. From multiple exposures of ozone to the same film, it was found that the number of active sites is large, greater than 1.4x1014 active sites per cm2 of surface area or comparable to the total number of surface sites. The films maintain some reactivity at this point, which is consistent with there being some degree of active site regeneration during the experiment and with ozone loss being catalytic to some degree. The initial uptake coefficients on fresh films were found to be inversely dependent on the ozone concentration, varying from roughly 10-6 for ozone concentrations of 1014 molecules/cm3 to 10-5 at 1013 molecules/cm3. The initial uptake coefficients were not dependent on the relative humidity, up to 75%, within the precision of the experiment. The reaction mechanism is discussed, as well as the implications these results have for assessing the effect of mineral dust on atmospheric oxidant levels.

Few studies have investigated the association between genetic variation and obesity traits in Indian populations or the role of environmental factors as modifiers of these relationships. In the context of rapid urbanisation, resulting in significant lifestyle changes, understanding the aetiology of obesity is important. We investigated associations of FTO and MC4R variants with obesity traits in 3390 sibling pairs from four Indian cities, most of whom were discordant for current dwelling (rural or urban). The FTO variant rs9939609 predicted increased weight (0.09 Z-scores, 95% CI: 0.03, 0.15) and BMI (0.08 Z-scores, 95% CI: 0.02, 0.14). The MC4R variant rs17782313 was weakly associated with weight and hip circumference (P

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